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Irrigator Pro

    Irrigator Pro is an expert system designed to provide irrigation scheduling recommendations based on scientific data resulting in conservation minded irrigation management. The success of Irrigator Pro for Peanuts created interest in other groups. A collaborative effort between the NPRL, Cotton Commission, University of Georgia, and the Peanut Foundation was established to create comparable models for cotton and corn.

    SWAGMAN-Whatif

      An interactive computer program was developed to simulate the interactions among the above factors. It shows how changing one factor impacts the outcome of the other factors for a single growing season. The user selects a climate, a crop, and soil characteristics from menu lists, and then sets the water table depth and quality, irrigation (river or well) water quality and then develops an irrigation schedule. On execution, the relative yield reductions due to over irrigation, under irrigation, and salinity, water table rise or fall and surface runoff are shown numerically for the growing season. Soil water content, soil salinity, water table depth changes and rain and irrigation events during the season are also shown graphically.

      Stream Temperature Modeling and Monitoring: Air Temperature Based Thermal Stream Habitat Model

        The Air Temperature Based Thermal Stream Habitat Model was originally developed from weather station information across the Columbia River basin in the Pacific Northwest. Multiple regression was used to predict mean annual air temperatures from elevation, latitude, and longitude with good success R^2 ~ 0.89). The model was developed as an alternative to PRISM data interpolations based on spline surface smoothing and should more accurately represent thermal conditions in stream valleys.

        Stream Temperature Modeling and Monitoring: Multiple Regression Stream Temperature Model

          This simple Stream Temperature Modeling and Monitoring approach uses thermograph data and geomorphic predictor variables from GIS software and digital elevation models (DEM). Multiple regression models are used to predict stream temperature metrics throughout a stream network with moderate accuracy (R^2 ~ 0.65). The models can provide basic descriptions of spatial patterns in stream temperatures, suitable habitat distributions for aquatic species, or be used to assess temporal trends related to climate or management activities if multiple years of temperature data are available.

          NorWeST Stream Temperature Regional Database and Model

            The NorWeST webpage hosts stream temperature data and climate scenarios in a variety of user-friendly digital formats for streams and rivers across the western U.S. Temperature data and model outputs, registered to NHDPlus stream lines, are posted to the website after QA/QC procedures and development of the final temperature model within a river basin.

            The National Stream Internet project

              National Stream Internet (NSI) project was developed as a means of providing a consistent, flexible analytical infrastructure that can be applied with many types of stream data anywhere in the country. A key part of that infrastructure is the NSI network, a digital GIS layer which has a specific topological structure that was designed to work effectively with SSNMs. The NSI network was derived from the National Hydrography Dataset Plus, Version 2 (NHDPlusV2) following technical procedures that ensure compatibility with SSNMs.

              The Aquatic eDNAtlas Project: Lab Results Map - USFS RMRS

                The eDNA samples in the eDNAtlas database describe species occurrence locations and were collected by the U.S. Forest Service and numerous agencies that have partnered with the National Genomics Center for Wildlife and Fish Conservation (NGC) throughout the United States. The eDNAtlas is accessed via an interactive ArcGIS Online (AGOL) map that allows users to view and download sample site information and lab results of species occurrence for the U.S. The results are primarily based on samples analyzed at the National Genomics Center for Wildlife and Fish Conservation (NGC) and associated with geospatial attributes created by the Boise Spatial Streams Group (BSSG).