John T Delaney

This data release contains the climate change model inputs and Soil and Water Assessment Tool (SWAT) model outputs from 360 HUC-8 watersheds in the Midwest United States (Illinois, Indiana, Iowa, Michigan, Minnesota, Ohio, and Wisconsin), that were generated using the HAWQS (Hydrologic and Water Quality System) platform (https://hawqs.tamu.edu). The summarized data for a watershed-based climate change vulnerability assessment for U.S. Fish and Wildlife Service is also provided, along with the R code used to summarize the raw outputs. Watershed-based Midwest Climate Change Vulnerability Assessment Tool: https://rconnect.usgs.gov/CC_Vulnerabi

Tags: Aquatic Biology, Climatology, Information Sciences, Land Use Change, Limnology, All tags... USGS Science Data Catalog (SDC), Water Quality, Water Resources, Wildlife Biology, Fewer tags

Watershed-based Midwest Climate Change Vulnerability Assessment Tool

Climate change has altered and is projected to continue to altering historic regimes of temperature, precipitation, and hydrology. To better understand the combined impacts of climate change from a land management perspective and spatially identify where the most extreme changes are anticipated to occur, we worked in collaboration with United States Fish and Wildlife Service managers to develop a climate change vulnerability map for the Midwestern United States. The map is intended to aid in the prioritization of locations needing support for adaptation planning and to help managers grapple with the impacts that projected climate scenarios have on the hydrology of management units as they develop adaptation strategies....

Future climate conditions in the Upper Mississippi River Basin are projected to include many more extreme precipitation events. These intense periods of rain can lead to flooding of the Mississippi River itself, as well the small streams and rivers that feed it. This flooding presents a challenge for local communities, farmers, small businesses, river users, and the ecosystems and wildlife in the area. To reduce the damage done by these extreme rainfall events, ‘natural solutions’ are often helpful. This might include preserving forests and grasslands to absorb rainwater before it arrives at streams or restoring wetlands to slow and clean runoff water. For river and natural resource managers to adapt to future climate...

Categories: Project; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: 2022, CASC, Drought, Fire and Extreme Weather, Drought, Fire and Extreme Weather, Extreme Weather, All tags... Extreme Weather, Midwest, Midwest CASC, Other Water, Projects by Region, Rivers, Streams and Lakes, Rivers, Streams and Lakes, Science Tools for Managers, Science Tools for Managers, Social Science, Social Science, State of the Science, Water, Coasts and Ice, Water, Coasts and Ice, Fewer tags

Daily HAWQS/SWAT Outputs along with Climate Inputs for USFWS Region 3 HUC-8 Watersheds

This dataset contains the input (temperature and precipitation from climate models) and output from the Soil and Water Assessment Tool (SWAT) model runs using the Hydrologic and Water Quality System (HAWQS) platform (https://hawqs.tamu.edu/). The HAWQS platform is an online tool developed by Texas A&M and US EPA to allow scientists and decision-makers to run large scale watershed simulation models using the Soil & Water Assessment Tool (SWAT) model without the need to download/install software, gather input data, perform initialization steps, or use up local computer resources. We ran the model at the Hydrologic Unit Code-8 scale over Region 3 of the United States Fish and Wildlife Service (Illinois, Indiana, Iowa,...

Tags: Adaptation Planning, Climate Change Vulnerability Assessment, Decision-Relevant Metrics, Watershed Model, biota

Predictions for the presence of submersed aquatic vegetation in the upper Mississippi River, USA, from years 2010-2019

The datasets are to accompany a manuscript describing the prediction of submersed aquatic vegetation presence and its potential vulnerability and recovery potential. The data and accompanying analysis scripts allow users to run the final random forests predictive model and reproduce the figures reported in the manuscript. Files from several data sources (aqa_2010_lvl3_pct_oute_joined_VEG_BARCODE.csv, eco_states_near_SAV.csv, ltrm_vegsrs_thru2019_GEOMORPHIC_METRICS_final.csv, vegetation_data.csv, and water_full.csv) were combined into a single .csv file (analysis_data_for_SAV_RandomForest.csv) used as the input for the random forest model. When intersecting points with geomorphic metrics some sites were moved slightly...

Categories: Data; Tags: Aquatic Biology, Ecology, Mississippi River, Pool 13, Pool 4, All tags... Pool 8, USGS Science Data Catalog (SDC), Water Resources, biota, ecosystem state, machine learning, macrophyte, predictive model, random forest, resilience, submergent plant, submersed plant, upper Mississippi River, vulnerability, Fewer tags