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Topography is a fundamental input to hydrologic models critical for generating realistic streamflow networks as well as infiltration and groundwater flow. Although there exist several national topographic datasets for the United States, they may not be compatible with gridded models that require hydrologically consistent digital elevation models (DEMs). Here, we present a national topographic dataset developed to support gridded hydrologic simulations at 1 km and 250 m spatial resolution over the contiguous United States. The workflow is described step by step in two parts: (a) DEM processing using a Priority Flood algorithm to ensure hydrologically consistent drainage networks and (b) slope calculation and smoothing to improve drainage performance. The accuracy of the derived stream network is evaluated by comparing the derived drainage area to drainage areas reported by the national stream gage network. The slope smoothing steps are evaluated using the runoff simulations with an integrated hydrologic model. Our DEM product started from the National Water Model DEM to ensure our final datasets will be as consistent as possible with this existing national framework. Our analysis shows that the additional processing we provide improves the consistency of simulated drainage areas and the runoff simulations that simulate gridded overland flow (as opposed to a network routing scheme). The workflow uses an open-source R package, and all output datasets and processing scripts are available and fully documented. All of the output datasets and scripts for processing are published through CyVerse at 250 m and 1 km resolution. The DOI link for the dataset is 10.25739/e1ps-qy48 (Zhang and Condon, 2020). [ABSTRACT FROM AUTHOR]

Topography is a fundamental input to hydrologic models critical for generating realistic streamflow networks as well as infiltration and groundwater flow. Although there exist several national topographic datasets for the United States, they may not be compatible with gridded models that require hydrologically consistent Digital Elevation Models (DEMs). Here, we present a national topographic dataset developed support physically based hydrologic simulations at 1km and 250m spatial resolution over contiguous United States. The workflow is described step-by-step in two parts (a) DEM processing using a Priority Flood algorithm to ensure hydrologically consistent drainage networks and (b) slope calculation and smoothing to improve drainage performance. The accuracy of derived stream network is evaluated by comparing the derived drainage area to drainage areas reported by the national stream gage network. The slope smoothing steps are evaluated using the runoff simulations with an integrated hydrologic model. The processed DEM is designed to capture the topographic features and improve the runoff simulations for the models solving partial differential equations. The workflow uses an open-source R package and all output datasets and processing scripts are available and fully documented here. All of the output datasets and scripts for processing are published through Cyverse at 250m and 1km resolution. [ABSTRACT FROM AUTHOR]

Understanding freshwater fluxes at continental scales will help us better predict hydrologic response and manage our terrestrial water resources. The partitioning of evapotranspiration into bare soil evaporation and plant transpiration remains a key uncertainty in the terrestrial water balance.We used integrated hydrologic simulations that couple vegetation and land-energy processes with surface and subsurface hydrology to study transpiration partitioning at the continental scale. Both latent heat flux and partitioning are connected to water table depth, and including lateral groundwater flow in the model increases transpiration partitioning from 47 ± 13 to 62 ± 12%.This suggests that lateral groundwater flow, which is generally simplified or excluded in Earth system models, may provide a missing link for reconciling observations and global models of terrestrial water fluxes. [ABSTRACT FROM AUTHOR]

• The ParFlow CONUS modeling platform is a large-scale, hyper-resolution, integrated surface-water and groundwater model. • The roughly five years of technical development of the latest ParFlow CONUS 2.0 platform is presented in this study. • Simulated steady-state water table depth and streamflow by CONUS 2.0 were evaluated using more than 635 K USGS observations and other compiled datasets. • Our results demonstrate improvement in both groundwater and surface water simulations over CONUS 1.0 for all USGS Hydrologic Unit Code (HUC) basins. • ParFlow CONUS models demonstrate better groundwater performance than previous large-scale groundwater models. Large-scale, high-resolution hydrologic modeling is an important tool to address questions of water quantity, availability, and potential recharge. Continental-to-Global scale models, particularly those that include groundwater, are growing in number. However, many of these approaches simplify aspects of the system and the connections between surface water and groundwater. The ParFlow CONUS modeling platform is a large-scale, hyper-resolution, hydrologic model that relies on the integrated solution of 3D partial differential equations that describe groundwater, soil, and 2D surface water flow. The prior version, ParFlow CONUS 1.0, was the first large-scale hydrologic model that included an explicit treatment of lateral groundwater flow for the contiguous US (CONUS). Here, we present the ParFlow CONUS 2.0 integrated hydrologic model. This model extends to the coastlines and contributing basins for CONUS and is consistent with the NOAA National Water Model. Here we document the roughly five years of technical development of this platform, present steady-state simulation results, rigorously compare these results to the prior ParFlow CONUS 1.0 simulations, and evaluate the model performance based on observations. Simulated water table depth and streamflow were evaluated using more than 635 K observations from USGS monitoring wells, other compiled groundwater datasets, and NHD and USGS streamflow gauges. Our results demonstrate improvement in both groundwater and surface water simulations over the prior generation model for all USGS Hydrologic Unit Code (HUC) basins. These results suggest that this current generation hydrologic model has good to excellent streamflow performance over the entire CONUS, with almost half of the HUC subbasins exhibiting excellent performance based on normalized root-square error (RSR). These results suggest that the current generation model approaches good performance for water table depth over the CONUS, a metric not usually compared directly at all in large-scale studies, with good-to-excellent performance exhibited over some HUC regions. We also delineate two regions that influence model performance, one where microtopography around streams dominates (D2), and another where a mix of subsurface heterogeneity and topographic gradients dominate (D1). Improvements in topography from CONUS1 to CONUS2 generally result in better streamflow and water table depth performances. Advancements in the subsurface depth and structure also produce better water table estimates. [ABSTRACT FROM AUTHOR]

In mountain, snow driven catchments, snowmelt is supposed to be the primary contribution to river streamflows during spring. In these catchments the contribution of groundwater is not well documented because of the difficulty to monitor groundwater in such complex environment with deep aquifers. In this study we use an integrated hydrologic model to conduct numerical experiments that help quantify the effect of lateral groundwater flow on total annual and peak streamflow in predevelopment conditions. Our simulations focus on the Upper Colorado River Basin (UCRB; 2.8 × 105 km2) a well‐documented mountain catchment for which both streamflow and water table measurements are available for several important sub‐basins. For the simulated water year, our results suggest an increase in peak flow of up to 57% when lateral groundwater flow processes are included—an unexpected result for flood conditions generally assumed independent of groundwater. Additionally, inclusion of lateral groundwater flow moderately improved the model match to observations. The correlation coefficient for mean annual flows improved from 0.84 for the no lateral groundwater flow simulation to 0.98 for the lateral groundwater flow one. Spatially we see more pronounced differences between lateral and no lateral groundwater flow cases in areas of the domain with steeper topography. We also found distinct differences in the magnitude and spatial distribution of streamflow changes with and without lateral groundwater flow between Upper Colorado River Sub‐basins. A sensitivity test that scaled hydraulic conductivity over two orders of magnitude was conducted for the lateral groundwater flow simulations. These results show that the impact of lateral groundwater flow is as large or larger than an order of magnitude change in hydraulic conductivity. While our results focus on the UCRB, we feel that these simulations have relevance to other headwaters systems worldwide. [ABSTRACT FROM AUTHOR]

Surface flow and subsurface flow constitute a naturally linked hydrologic continuum that has not traditionally been simulated in an integrated fashion. Recognizing the interactions between these systems has encouraged the development of integrated hydrologic models (IHMs) capable of treating surface and subsurface systems as a single integrated resource. IHMs are dynamically evolving with improvements in technology, and the extent of their current capabilities are often only known to the developers and not general users. This article provides an overview of the core functionality, capability, applications, and ongoing development of one open-source IHM, ParFlow. ParFlow is a parallel, integrated, hydrologic model that simulates surface and subsurface flows. ParFlow solves the Richards equation for three-dimensional variably saturated groundwater flow and the two-dimensional kinematic wave approximation of the shallow water equations for overland flow. The model employs a conservative centered finite-difference scheme and a conservative finite-volume method for subsurface flow and transport, respectively. ParFlow uses multigrid-preconditioned Krylov and Newton–Krylov methods to solve the linear and nonlinear systems within each time step of the flow simulations. The code has demonstrated very efficient parallel solution capabilities. ParFlow has been coupled to geochemical reaction, land surface (e.g., the Common Land Model), and atmospheric models to study the interactions among the subsurface, land surface, and atmosphere systems across different spatial scales. This overview focuses on the current capabilities of the code, the core simulation engine, and the primary couplings of the subsurface model to other codes, taking a high-level perspective. [ABSTRACT FROM AUTHOR]