The Minnesota DNR Toolbox and Hydro Tools provide a number of convenience geoprocessing tools used regularly by MNDNR staff. Many of these may be useful to the wider public. However, some tools may rely on data that is not available outside of the DNR. All tools require at least ArcGIS 10+.

If you create a GDRS using GDRS Manager and include this toolbox resource and MNDNR Quick Layers, the DNR toolboxes will automatically be added to the ArcToolbox window whenever Quick Layers GDRS Location is set to the GDRS location that has the toolboxes.

Toolsets included in MNDNR Tools V10:
- Analysis Tools
- Conversion Tools
- Division Tools
- General Tools
- Hydrology Tools
- LiDAR and DEM Tools
- Raster Tools
- Sampling Tools

These toolboxes are provided free of charge and are not warrantied for any specific use. We do not provide support or assistance in downloading or using these tools. We do, however, strive to produce high-quality tools and appreciate comments you have about them.

Succeeds and combines earlier versions of the tools - Topography Toolbox for ArcGIS 9.x - http://arcscripts.esri.com/details.asp?dbid=15996Riparian Topography Toolbox for calculating Height Above River and Height Above Nearest Drainage - http://arcscripts.esri.com/details.asp?dbid=16792PRISM Data Helper - http://arcscripts.esri.com/details.asp?dbid=15976Tools:UplandBeer’s AspectMcCune and Keon Heat Load IndexLandform ClassifcationPRISM Data HelperSlope Position ClassificationSolar Illumination IndexTopographic Convergence/Wetness IndexTopographic Position IndexRiparianDerive Stream Raster using Cost DistanceHeight Above Nearest DrainageHeight Above RiverMiscellaneousMoving Window Correlation

Deprecation notice: This tool is deprecated because this functionality is now available with out-of-the-box tools in ArcGIS Pro. The tool author will no longer be making further enhancements or fixing major bugs.Use Add GTFS to a Network Dataset to incorporate transit data into a network dataset so you can perform schedule-aware analyses using the Network Analyst tools in ArcMap.After creating your network dataset, you can use the ArcGIS Network Analyst tools, like Service Area and OD Cost Matrix, to perform transit/pedestrian accessibility analyses, make decisions about where to locate new facilities, find populations underserved by transit or particular types of facilities, or visualize the areas reachable from your business at different times of day. You can also publish services in ArcGIS Server that use your network dataset.The Add GTFS to a Network Dataset tool suite consists of a toolbox to pre-process the GTFS data to prepare it for use in the network dataset and a custom GTFS transit evaluator you must install that helps the network dataset read the GTFS schedules. A user's guide is included to help you set up your network dataset and run analyses.Instructions:Download the tool. It will be a zip file.Unzip the file and put it in a permanent location on your machine where you won't lose it. Do not save the unzipped tool folder on a network drive, the Desktop, or any other special reserved Windows folders (like C:\Program Files) because this could cause problems later.The unzipped file contains an installer, AddGTFStoaNetworkDataset_Installer.exe. Double-click this to run it. The installation should proceed quickly, and it should say "Completed" when finished.Read the User's Guide for instructions on creating and using your network dataset.System requirements:ArcMap 10.1 or higher with a Desktop Standard (ArcEditor) license. (You can still use it if you have a Desktop Basic license, but you will have to find an alternate method for one of the pre-processing tools.) ArcMap 10.6 or higher is recommended because you will be able to construct your network dataset much more easily using a template rather than having to do it manually step by step. This tool does not work in ArcGIS Pro. See the User's Guide for more information.Network Analyst extensionThe necessary permissions to install something on your computer.Data requirements:Street data for the area covered by your transit system, preferably data including pedestrian attributes. If you need help preparing high-quality street data for your network, please review this tutorial.A valid GTFS dataset. If your GTFS dataset has blank values for arrival_time and departure_time in stop_times.txt, you will not be able to run this tool. You can download and use the Interpolate Blank Stop Times tool to estimate blank arrival_time and departure_time values for your dataset if you still want to use it.Help forum

Use the Attachment Viewer template to provide an app for users to explore a layer's features and review attachments with the option to update attribute data. Present your images, videos, and PDF files collected using ArcGIS Field Maps or ArcGIS Survey123 workflows. Choose an attachment-focused layout to display individual images beside your map or a map-focused layout to highlight your map next to a gallery of images. Examples: Review photos collected during emergency response damage inspections. Display the results of field data collection and support downloading images for inclusion in a report. Present a map of land parcel along with associated documents stored as attachments. Data requirements The Attachment Viewer template requires a feature layer with attachments. It includes the capability to view attachments of a hosted feature service or an ArcGIS Server feature service (10.8 or later). Currently, the app can display JPEG, JPG, PNG, GIF, MP4, QuickTime (.mov), and PDF files in the viewer window. All other attachment types are displayed as a link. Key app capabilities App layout - Choose between an attachment-focused layout, which displays one attachment at a time in the main panel of the app with the map on the side, or a map-focused layout, which displays the map in the main panel of the app with a gallery of attachments. Feature selection - Allows users to select features in the map and view associated attachments. Review data - Enable tools to review and update existing records. Zoom, pan, download images - Allow users to interact with and download attachments. Language switcher - Provide translations for custom text and create a multilingual app. Home, Zoom controls, Legend, Layer List, Search Supportability This web app is designed responsively to be used in browsers on desktops, mobile phones, and tablets. We are committed to ongoing efforts towards making our apps as accessible as possible. Please feel free to leave a comment on how we can improve the accessibility of our apps for those who use assistive technologies.

The Grid Garage Toolbox is designed to help you undertake the Geographic Information System (GIS) tasks required to process GIS data (geodata) into a standard, spatially aligned format. This format is required by most, grid or raster, spatial modelling tools such as the Multi-criteria Analysis Shell for Spatial Decision Support (MCAS-S). Grid Garage contains 36 tools designed to save you time by batch processing repetitive GIS tasks as well diagnosing problems with data and capturing a record of processing step and any errors encountered.

Grid Garage provides tools that function using a list based approach to batch processing where both inputs and outputs are specified in tables to enable selective batch processing and detailed result reporting. In many cases the tools simply extend the functionality of standard ArcGIS tools, providing some or all of the inputs required by these tools via the input table to enable batch processing on a 'per item' basis. This approach differs slightly from normal batch processing in ArcGIS, instead of manually selecting single items or a folder on which to apply a tool or model you provide a table listing target datasets. In summary the Grid Garage allows you to:

• List, describe and manage very large volumes of geodata.
• Batch process repetitive GIS tasks such as managing (renaming, describing etc.) or processing (clipping, resampling, reprojecting etc.) many geodata inputs such as time-series geodata derived from satellite imagery or climate models.
• Record any errors when batch processing and diagnose errors by interrogating the input geodata that failed.
• Develop your own models in ArcGIS ModelBuilder that allow you to automate any GIS workflow utilising one or more of the Grid Garage tools that can process an unlimited number of inputs.
• Automate the process of generating MCAS-S TIP metadata files for any number of input raster datasets.

The Grid Garage is intended for use by anyone with an understanding of GIS principles and an intermediate to advanced level of GIS skills. Using the Grid Garage tools in ArcGIS ModelBuilder requires skills in the use of the ArcGIS ModelBuilder tool.

Download Instructions: Create a new folder on your computer or network and then download and unzip the zip file from the GitHub Release page for each of the following items in the 'Data and Resources' section below. There is a folder in each zip file that contains all the files. See the Grid Garage User Guide for instructions on how to install and use the Grid Garage Toolbox with the sample data provided.

This is a link to the QGIS website where you can download open-source GIS software for viewing, analyzing and manipulating geodata like our downloadable shapefiles.

The Travel Time Tool was created by the MN DNR to use GIS analysis for calculation of hydraulic travel time from gridded surfaces and develop a downstream travel time raster for each cell in a watershed. This hydraulic travel time process, known as Time of Concentration, is a concept from the science of hydrology that measures watershed response to a precipitation event. The analysis uses watershed characteristics such as land-use, geology, channel shape, surface roughness, and topography to measure time of travel for water. Described as Travel Time, it calculates the elapsed time for a simulated drop of water to migrate from its source along a hydraulic path across different surfaces of the replicated watershed landscape, ultimately reaching the watershed outlet. The Travel Time Tool creates a raster whereas each cell is a measure of the length of time (in seconds) that it takes water to flow across it, and then accumulates the time (in hours) from the cell to the outlet of the watershed.

The Travel Time Tool creates an impedance raster from Manning's Equation that determines the velocity of water flowing across the cell as a measure of time (in feet per second). The Flow Length Tool uses the travel time Grid for the impedance factor and determines the downstream flow time from each cell to the outlet of the watershed.

The toolbox works with ArcMap 10.6.1 and newer and ArcGIS Pro.

For step-by-step instructions on how to use the tool, please view MN DNR Travel Time Guidance.pdf

This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

ssurgoOnDemandThe purpose of these tools are to give users the ability to get Soil Survey Geographic Database (SSURGO) properties and interpretations in an efficient manner. They are very similiar to the United States Department of Agriculture - Natural Resource Conservation Service's distributed Soil Data Viewer (SDV), although there are distinct differences. The most important difference is the data collected with the SSURGO On-Demand (SOD) tools are collected in real-time via web requests to Soil Data Access (https://sdmdataaccess.nrcs.usda.gov/). SOD tools do not require users to have the data found in a traditional SSURGO download from the NRCS's official repository, Web Soil Survey (https://websoilsurvey.sc.egov.usda.gov/App/HomePage.htm). The main intent of both SOD and SDV are to hide the complex relationships of the SSURGO tables and allow the users to focus on asking the question they need to get the information they want. This is accomplished in the user interface of the tools and the subsequent SQL is built and executed for the user. Currently, the tools packaged here are designed to run within the ESRI ArcGIS Desktop Application - ArcMap, version 10.1 or greater. However, much of the Python code is recyclable and could run within a Python intepreter or other GIS applications such as Quantum GIS with some modification.NOTE: The queries in these tools only consider the major components of soil map units.Within the SOD tools are 2 primary toolsets, descibed as follows:<1. AreasymbolThe Areasymbol tools collect SSURGO properties and interpretations based on a user supplied list of Soil Survey areasymbols (e.g. NC123). After the areasymbols have been collected, an aggregation method (see below) is selected . Tee aggregation method has no affect on interpretations other than how the SSURGO data aggregated. For soil properties, the aggregation method drives what properties can be run. For example, you can't run the weighted average aggregation method on Taxonomic Order. Similarly, for the same soil property, you wouldn't specify a depth range. The point here is the aggregation method affects what parameters need to be supplied for the SQL generation. It is important to note the user can specify any number of areasymbols and any number of interpretations. This is another distinct advantage of these tools. You could collect all of the SSURGO interpretations for every soil survey area (areasymbol) by executing the tool 1 time. This also demonstrates the flexibility SOD has in defining the geographic extent over which information is collected. The only constraint is the extent of soil survey areas selected to run (and these can be discontinuous).As SOD Areasymbol tools execute, 2 lists are collected from the tool dialog, a list of interpretations/properties and a list of areasymbols. As each interpretation/property is run, every areasymbol is run against the interpretation/property requested. For instance, suppose you wanted to collect the weighted average of sand, silt and clay for 5 soil survey areas. The sand property would run for all 5 soil survey areas and built into a table. Next the silt would run for all 5 soil survey areas and built into a table, and so on. In this example a total of 15 web request would have been sent and 3 tables are built. Two VERY IMPORTANT things here...A. All the areasymbol tools do is generate tables. They are not collecting spatial data.B. They are collecting stored information. They are not making calculations(with the exception of the weighted average aggregation method).<2. ExpressThe Express toolset is nearly identical to the Areasymbol toolset, with 2 exceptions.A. The area to collect SSURGO information over is defined by the user. The user digitizes coordinates into a 'feature set' after the tool is open. The points in the feature set are closed (first point is also the last) into a polygon. The polygon is sent to Soil Data Access and the features set points (polygon) are used to clip SSURGO spatial data. The geomotries of the clip operation are returned, along with the mapunit keys (unique identifier). It is best to keep the points in the feature set simple and beware of self intersections as they are fatal.B. Instead of running on a list of areasymbols, the SQL queries on a list of mapunit keys.The properties and interpretations options are identical to what was discussed for the Areasymbol toolset.The Express tools present the user the option of creating layer files (.lyr) where the the resultant interpretation/property are joined to the geometry and saved to disk as a virtual join. Additionally, for soil properties, an option exists to append all of the selected soil properties to a single table. In this case, if the user ran sand, silt, and clay properties, instead of 3 output tables, there is only 1 table with a sand column, a silt column, and a clay column.<Supplemental Information<sAggregation MethodAggregation is the process by which a set of component attribute values is reduced to a single value to represent the map unit as a whole.A map unit is typically composed of one or more "components". A component is either some type of soil or some nonsoil entity, e.g., rock outcrop. The components in the map unit name represent the major soils within a map unit delineation. Minor components make up the balance of the map unit. Great differences in soil properties can occur between map unit components and within short distances. Minor components may be very different from the major components. Such differences could significantly affect use and management of the map unit. Minor components may or may not be documented in the database. The results of aggregation do not reflect the presence or absence of limitations of the components which are not listed in the database. An on-site investigation is required to identify the location of individual map unit components. For queries of soil properties, only major components are considered for Dominant Component (numeric) and Weighted Average aggregation methods (see below). Additionally, the aggregation method selected drives the available properties to be queried. For queries of soil interpretations, all components are condisered.For each of a map unit's components, a corresponding percent composition is recorded. A percent composition of 60 indicates that the corresponding component typically makes up approximately 60% of the map unit. Percent composition is a critical factor in some, but not all, aggregation methods.For the attribute being aggregated, the first step of the aggregation process is to derive one attribute value for each of a map unit's components. From this set of component attributes, the next step of the aggregation process derives a single value that represents the map unit as a whole. Once a single value for each map unit is derived, a thematic map for soil map units can be generated. Aggregation must be done because, on any soil map, map units are delineated but components are not.The aggregation method "Dominant Component" returns the attribute value associated with the component with the highest percent composition in the map unit. If more than one component shares the highest percent composition, the value of the first named component is returned.The aggregation method "Dominant Condition" first groups like attribute values for the components in a map unit. For each group, percent composition is set to the sum of the percent composition of all components participating in that group. These groups now represent "conditions" rather than components. The attribute value associated with the group with the highest cumulative percent composition is returned. If more than one group shares the highest cumulative percent composition, the value of the group having the first named component of the mapunit is returned.The aggregation method "Weighted Average" computes a weighted average value for all components in the map unit. Percent composition is the weighting factor. The result returned by this aggregation method represents a weighted average value of the corresponding attribute throughout the map unit.The aggregation method "Minimum or Maximum" returns either the lowest or highest attribute value among all components of the map unit, depending on the corresponding "tie-break" rule. In this case, the "tie-break" rule indicates whether the lowest or highest value among all components should be returned. For this aggregation method, percent composition ties cannot occur. The result may correspond to a map unit component of very minor extent. This aggregation method is appropriate for either numeric attributes or attributes with a ranked or logically ordered domain.

Download Report Card Data File GeodatabaseThese data contain feature classes that are used in the Virginia GIS Data Report Card Tools for NG9-1-1 Preparation.Seeherefor the user guide and tools.Additionalresources and recommendations on GIS related topics are available on theVGIN 9-1-1 & GISpage.

GIS – Great Lakes Sediment Budget – Technical Methodology – Buffline Digitization Madeleine Dewey EIT1 , Cedric Wrobel EIT1 1United States Army Corps of Engineers Great Lakes and Ohio River Division, Buffalo District Department of Coastal and Geotechnical Design Editor and Senior Reviewer: Weston Cross PG1 Published: September 2021 Abstract: This document is intended for use as a reference guide to complete bluffline digitization work for the Great Lakes Sediment Budget, a project of the Great Lakes Restoration Initiative. Digitization work consists of manually drawing polylines along the lakeshore to delineate where the bluffline, or more broadly, the line of significance, exists. This reference can be used for both historic, and contemporary blufflines. In addition, this guide outlines what datasets, ESRI ArcGIS tools, and strategies should be employed. The manual for ESRI ArcMap 10.7, the version of ArcGIS used to create this guide, can be found at: https://support.esri.com/en/products/desktop/arcgis‐desktop/arcmap/10‐7‐1

This is the DEM data for the watershed boundary for French Broad River near Newport. This resource includes one TIFF image presenting the projected DEM data of watershed boundary for French Broad River Near Newport and one txt file containing the Python code used to download and process the original DEM data. The input data is http://www.hydroshare.org/resource/860155baa06d46f1a0c3e0bf48e9b348 , provided by Dr. Venkatesh Merwade. The code has some minor problems with the last line of Cell 7. Currently it can download, merge and project the DEM data and save them as TIFF file. We're still working on clipping the TIFF image so it can be complete. To run the code, read the instructions in readme.txt.

This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independently of ArcMap, but output is then limited to a tabular report. The soil survey attribute database associated with the spatial soil map is a complicated database with more than 50 tables. Soil Data Viewer provides users access to soil interpretations and soil properties while shielding them from the complexity of the soil database. Each soil map unit, typically a set of polygons, may contain multiple soil components that have different use and management. Soil Data Viewer makes it easy to compute a single value for a map unit and display results, relieving the user from the burden of querying the database, processing the data and linking to the spatial map. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Resources in this dataset:Resource Title: Soil Data Viewer. File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/home/?cid=nrcs142p2_053620 Soil Data Viewer is a tool built as an extension to ArcMap that allows a user to create soil-based thematic maps. The application can also be run independent of ArcMap, but output is then limited to a tabular report. Soil Data Viewer contains processing rules to enforce appropriate use of the data. This provides the user with a tool for quick geospatial analysis of soil data for use in resource assessment and management. Links to download and install Download Soil Data Viewer 6.2 for use with ArcGIS 10.x and Windows XP, Windows 7, Windows 8.x, or Windows 10. Earlier versions are also available.

NLEAP GIS 5.0 can help users identify hot spots across the landscape and identify management practices that can increase nitrogen use efficiency. A Nitrogen Trading Tool (NTT) analysis can be conducted to determine the potential benefits of implementing best management practices and the quantity of nitrogen savings that could potentially be traded in future air or water quality markets. Resources in this dataset:Resource Title: NLEAP GIS 5.0. File Name: Web Page, url: https://www.ars.usda.gov/research/software/download/?softwareid=428&modecode=30-12-30-15 download page

The Global Wind Atlas (GWA) is a free, web-based application developed to help policymakers, planners, and investors identify high-wind areas for wind power generation virtually anywhere in the world, and then perform preliminary calculations. The GWA facilitates online queries and provides freely downloadable datasets based on the latest input data and modeling methodologies. They perform a generalization process on large-scale wind climate data from atmospheric re-analysis data in the ERA5 dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF). The result is a set of generalized wind climates. Users can download high-resolution maps of the wind resource potential, for use in GIS tools.

The National Flood Hazard Layer (NFHL) is a geospatial database that contains current effective flood hazard data. FEMA provides the flood hazard data to support the National Flood Insurance Program. You can use the information to better understand your level of flood risk and type of flooding.The NFHL is made from effective flood maps and Letters of Map Change (LOMC) delivered to communities. NFHL digital data covers over 90 percent of the U.S. population. New and revised data is being added continuously. If you need information for areas not covered by the NFHL data, there may be other FEMA products which provide coverage for those areas.In the NFHL Viewer, you can use the address search or map navigation to locate an area of interest and the NFHL Print Tool to download and print a full Flood Insurance Rate Map (FIRM) or FIRMette (a smaller, printable version of a FIRM) where modernized data exists. Technical GIS users can also utilize a series of dedicated GIS web services that allow the NFHL database to be incorporated into websites and GIS applications. For more information on available services, go to the NFHL GIS Services User Guide.You can also use the address search on the FEMA Flood Map Service Center (MSC) to view the NFHL data or download a FIRMette. Using the “Search All Products” on the MSC, you can download the NFHL data for a County or State in a GIS file format. This data can be used in most GIS applications to perform spatial analyses and for integration into custom maps and reports. To do so, you will need GIS or mapping software that can read data in shapefile format.FEMA also offers a download of a KMZ (keyhole markup file zipped) file, which overlays the data in Google Earth™. For more information on using the data in Google Earth™, please see Using the National Flood Hazard Layer Web Map Service (WMS) in Google Earth™.

This dataset represents a water shortage vulnerability analysis performed by DWR using modified PLSS sections pulled from the Well Completion Report PLSS Section Summaries. The attribute table includes water shortage vulnerability indicators and scores from an analysis done by CA Department of Water Resources, joined to modified PLSS sections. Several relevant summary statistics from the Well Completion Reports are included in this table as well. This data is from the 2024 analysis.

Water Code Division 6 Part 2.55 Section 8 Chapter 10 (Assembly Bill 1668) effectively requires California Department of Water Resources (DWR), in consultation with other agencies and an advisory group, to identify small water suppliers and “rural communities” that are at risk of drought and water shortage. Following legislation passed in 2021 and signed by Governor Gavin Newsom, the Water Code Division 6, Section 10609.50 through 10609.80 (Senate Bill 552 of 2021) effectively requires the California Department of Water Resources to update the scoring and tool periodically in partnership with the State Water Board and other state agencies. This document describes the indicators, datasets, and methods used to construct this deliverable.  This is a statewide effort to systematically and holistically consider water shortage vulnerability statewide of rural communities, focusing on domestic wells and state small water systems serving between 4 and 14 connections. The indicators and scoring methodology will be revised as better data become available and stake-holders evaluate the performance of the indicators, datasets used, and aggregation and ranking method used to aggregate and rank vulnerability scores. Additionally, the scoring system should be adaptive, meaning that our understanding of what contributes to risk and vulnerability of drought and water shortage may evolve. This understanding may especially be informed by experiences gained while navigating responses to future droughts.”

A spatial analysis was performed on the 2020 Census Block Groups, modified PLSS sections, and small water system service areas using a variety of input datasets related to drought vulnerability and water shortage risk and vulnerability. These indicator values were subsequently rescaled and summed for a final vulnerability score for the sections and small water system service areas. The 2020 Census Block Groups were joined with ACS data to represent the social vulnerability of communities, which is relevant to drought risk tolerance and resources. These three feature datasets contain the units of analysis (modified PLSS sections, block groups, small water systems service areas) with the model indicators for vulnerability in the attribute table. Model indicators are calculated for each unit of analysis according to the Vulnerability Scoring documents provided by Julia Ekstrom (Division of Regional Assistance).

All three feature classes are DWR analysis zones that are based off existing GIS datasets. The spatial data for the sections feature class is extracted from the Well Completion Reports PLSS sections to be aligned with the work and analysis that SGMA is doing. These are not true PLSS sections, but a version of the projected section lines in areas where there are gaps in PLSS. The spatial data for the Census block group feature class is downloaded from the Census. ACS (American Communities Survey) data is joined by block group, and statistics calculated by DWR have been added to the attribute table. The spatial data for the small water systems feature class was extracted from the State Water Resources Control Board (SWRCB) SABL dataset, using a definition query to filter for active water systems with 3000 connections or less. None of these datasets are intended to be the authoritative datasets for representing PLSS sections, Census block groups, or water service areas. The spatial data of these feature classes is used as units of analysis for the spatial analysis performed by DWR.

These datasets are intended to be authoritative datasets of the scoring tools required from DWR according to Senate Bill 552. Please refer to the Drought and Water Shortage Vulnerability Scoring: California's Domestic Wells and State Smalls Systems documentation for more information on indicators and scoring. These estimated indicator scores may sometimes be calculated in several different ways, or may have been calculated from data that has since be updated. Counts of domestic wells may be calculated in different ways. In order to align with DWR SGMO's (State Groundwater Management Office) California Groundwater Live dashboards, domestic wells were calculated using the same query. This includes all domestic wells in the Well Completion Reports dataset that are completed after 12/31/1976, and have a 'RecordType' of 'WellCompletion/New/Production or Monitoring/NA'.

Please refer to the Well Completion Reports metadata for more information. The associated data are considered DWR enterprise GIS data, which meet all appropriate requirements of the DWR Spatial Data Standards, specifically the DWR Spatial Data Standard version 3.4, dated September 14, 2022. DWR makes no warranties or guarantees — either expressed or implied— as to the completeness, accuracy, or correctness of the data.

DWR neither accepts nor assumes liability arising from or for any incorrect, incomplete, or misleading subject data. Comments, problems, improvements, updates, or suggestions should be forwarded to GIS@water.ca.gov.

This dataset is a series of digital map-posters accompanying the AdaptNRM Guide: Helping Biodiversity Adapt: supporting climate adaptation planning using a community-level modelling approach.

These represent supporting materials and information about the community-level biodiversity models applied to climate change. Map posters are organised by four biological groups (vascular plants, mammals, reptiles and amphibians), two climate change scenario (1990-2050 MIROC5 and CanESM2 for RCP8.5), and five measures of change in biodiversity.

The map-posters present the nationally consistent data at locally relevant resolutions in eight parts – representing broad groupings of NRM regions based on the cluster boundaries used for climate adaptation planning (http://www.environment.gov.au/climate-change/adaptation) and also Nationally.

Map-posters are provided in PNG image format at moderate resolution (300dpi) to suit A0 printing. The posters were designed to meet A0 print size and digital viewing resolution of map detail. An additional set in PDF image format has been created for ease of download for initial exploration and printing on A3 paper. Some text elements and map features may be fuzzy at this resolution.

Each map-poster contains four dataset images coloured using standard legends encompassing the potential range of the measure, even if that range is not represented in the dataset itself or across the map extent.

Most map series are provided in two parts: part 1 shows the two climate scenarios for vascular plants and mammals and part 2 shows reptiles and amphibians. Eight cluster maps for each series have a different colour theme and map extent. A national series is also provided. Annotation briefly outlines the topics presented in the Guide so that each poster stands alone for quick reference.

An additional 77 National maps presenting the probability distributions of each of 77 vegetation types – NVIS 4.1 major vegetation subgroups (NVIS subgroups) - are currently in preparation.

Example citations:

Williams KJ, Raisbeck-Brown N, Prober S, Harwood T (2015) Generalised projected distribution of vegetation types – NVIS 4.1 major vegetation subgroups (1990 and 2050), A0 map-poster 8.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

Williams KJ, Raisbeck-Brown N, Harwood T, Prober S (2015) Revegetation benefit (cleared natural areas) for vascular plants and mammals (1990-2050), A0 map-poster 9.1 - East Coast NRM regions. CSIRO Land and Water Flagship, Canberra. Available online at www.AdaptNRM.org and https://data.csiro.au/dap/.

This dataset has been delivered incrementally. Please check that you are accessing the latest version of the dataset. Lineage: The map posters show case the scientific data. The data layers have been developed at approximately 250m resolution (9 second) across the Australian continent to incorporate the interaction between climate and topography, and are best viewed using a geographic information system (GIS). Each data layers is 1Gb, and inaccessible to non-GIS users. The map posters provide easy access to the scientific data, enabling the outputs to be viewed at high resolution with geographical context information provided.

Maps were generated using layout and drawing tools in ArcGIS 10.2.2

A check list of map posters and datasets is provided with the collection.

Map Series: 7.(1-77) National probability distribution of vegetation type – NVIS 4.1 major vegetation subgroup pre-1750 #0x

8.1 Generalised projected distribution of vegetation types (NVIS subgroups) (1990 and 2050)

9.1 Revegetation benefit (cleared natural areas) for plants and mammals (1990-2050)

9.2 Revegetation benefit (cleared natural areas) for reptiles and amphibians (1990-2050)

10.1 Need for assisted dispersal for vascular plants and mammals (1990-2050)

10.2 Need for assisted dispersal for reptiles and amphibians (1990-2050)

11.1 Refugial potential for vascular plants and mammals (1990-2050)

11.1 Refugial potential for reptiles and amphibians (1990-2050)

12.1 Climate-driven future revegetation benefit for vascular plants and mammals (1990-2050)

12.2 Climate-driven future revegetation benefit for vascular reptiles and amphibians (1990-2050)

DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

DNRGPS does not require installation. Simply run the application .exe

See the DNRGPS application documentation for more details.

Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.