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Data to support water quality modeling efforts in the Delaware River Basin: 1) Spatial data for rivers, reservoirs, and monitoring locations This data release contains information to support water quality modeling in the Delaware River Basin (DRB). These data support both process-based and machine learning approaches to water quality modeling, including the prediction of stream temperature. This section provides spatial data files that describe the rivers, reservoirs, and observational data in the Delaware River Basin included in this release. One shapefile of polylines describes the 459 river reaches that define the modeling network, and another shapefile of polygons includes the three reservoirs (Pepacton, Cannonsville, and Neversink) for which data are included in this release. Additionally, a point shapefile contains locations of monitoring sites... Categories: Data; Types: Downloadable, Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service, Shapefile; Tags: DE, Delaware, MD, Maryland, NJ, All tags... NY, New Jersey, New York, PA, Pennsylvania, US, United States, environment, inlandWaters, modeling, reservoirs, streams, temperature, water, water quality, water resources, Fewer tags CAST Data Input Disaggregation from County and Land-River Segment Scale to National Hydrography Dataset Plus, Version 1.1 The detrimental effects of excess nutrients and sediment entering the Chesapeake Bay estuary from its watersheds have necessitated regulatory actions. Federally-mandated reductions are apportioned to bay jurisdictions based on the U.S. Environmental Protection Agency's Chesapeake Bay Time-Variable Watershed Model (CBPM). The Chesapeake Assessment Scenario Tool (CAST version CAST-19; cast.chesapeakebay.net; Chesapeake Bay Program, 2020) is a simplified, on-line version of the Phase 6 CBPM that simulates watershed nutrients delivery to the estuary using the original model's annual land-surface nutrient source and removal inputs and time-averaged climatological forecasting. Because it runs much faster than the CBPM,... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: Atmospheric Deposition, Biosolids, Chesapeake, Chesapeake Assessment and Scenario Tool (CAST), Chesapeake Bay, All tags... Combined Sewer Overflow, DC, DE, Fertilizer, Land Use Change, MD, Manure, NY, National Hydrography Dataset (NHD), Nitrogen Fixation and Crop Nutrient Uptake, Nutrient Inputs, PA, USGS Science Data Catalog (SDC), VA, WV, Wastewater, Septic Systems, and Rapid Infiltration Basins, Water Quality, environment, nutrient cycling, Fewer tags Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin This data release and model archive provides all data, code, and modelling results used in Topp et al. (2023) to examine the influence of deep learning architecture on generalizability when predicting stream temperature in the Delaware River Basin (DRB). Briefly, we modeled stream temperature in the DRB using two spatially and temporally aware process guided deep learning models (a recurrent graph convolution network - RGCN, and a temporal convolution graph model - Graph WaveNet). The associated manuscript explores how the architectural differences between the two models influence how they learn spatial and temporal relationships, and how those learned relationships influence a model's ability to accurately predict... Categories: Data; Types: Map Service, OGC WFS Layer, OGC WMS Layer, OGC WMS Service; Tags: DE, Delaware, Hydrology, MD, Maryland, All tags... NJ, NY, New Jersey, New York, PA, Pennsylvania, US, USGS Science Data Catalog (SDC), United States, Water Quality, Water Resources, climate change, domain shift, environment, explainable AI (XAI), generalization, hybrid modeling, inlandWaters, machine learning, modeling, process guided deep learning, stream temperature, temperature, water, water resources, Fewer tags